A number of current electronic warfare support systems (ES) are used to classify vehicle tracks. One system monitors the electromagnetic radiation emitted by vehicles for the purpose of classifying the vehicles. Another system uses non-cooperative target recognition techniques (NCRT) such as jet engine modulation where a surveillance system directs energy at a vehicle and analyzes its reflected response for the purpose of classifying the target.
However, the current electronic warfare support systems have drawbacks. First, ES techniques require the vehicular track to be emitting previously classified patterns; common techniques for defeating ES analysis are to simply turn off any of the vehicle's transmitters, or to change to a new set of patterns held in reserve. NCTR techniques are also problematic including the aspect of the vehicle to the NCTR equipment. In addition, the current ES techniques do not fuse inputs from multiple sensor types, and do not associate events from different vehicles of different types to develop track classifications.
Thus, a rapid and accurate classification of vehicular tracks as a specific threat type is needed. Depth of fire and kill probability can both be improved with automated classification of potential threats, in particular of high-speed anti-ship cruise missiles, which pose a significant threat to naval combatants. These improvements can be obtained through more rapid classification and also through more reliable classification.